Upload 6 files

app.py

@@ -51,11 +51,16 @@ def upload_pdf(files):
 
 
 
+# Load QG and QA once
+qgen = QGenerator()
+qa_model = pipeline("text2text-generation", model="google/flan-t5-base")
 def generate_qa(token):
     try:
         if not token:
             return "⚠️ Please provide a token."
 
+        print("📥 Received Token:", token)
+
         # Load chunk_data using token
         with sqlite3.connect("my_database.db") as conn:
             cursor = conn.cursor()
@@ -63,41 +68,59 @@ def generate_qa(token):
             row = cursor.fetchone()
 
         if not row:
+            print("❌ No data found for token in DB.")
             return "❌ No data found for this token."
 
         chunks = json.loads(row[0])
+        if not chunks:
+            print("⚠️ Chunk data is empty.")
+            return "⚠️ No content available in database for this PDF."
+
         qa_pairs = []
 
-        for chunk in chunks:
+        for i, chunk in enumerate(chunks):
+            print(f"\n🔹 Processing chunk {i+1}/{len(chunks)}")
             questions = qgen.generate(chunk)
+            print(f"🧠 Questions generated: {questions}")
+
             if not questions:
+                print("⚠️ No questions generated for this chunk.")
                 continue
 
             for question in questions[:2]:  # Max 2 Qs per chunk
                 prompt = f"Context: {chunk}\n\nQuestion: {question}\n\nAnswer:"
+                print(f"➡️ Prompt:\n{prompt}")
+
                 try:
                     result = qa_model(prompt, max_length=256, do_sample=False)
+                    print(f"⬅️ Raw model output: {result}")
+
                     if isinstance(result, list) and "generated_text" in result[0]:
                         answer = result[0]["generated_text"].strip()
                     elif isinstance(result, dict) and "answer" in result:
                         answer = result["answer"].strip()
                     else:
                         answer = "N/A"
+
+                    print(f"✅ Final Answer: {answer}")
                     qa_pairs.append(f"Q: {question}\nA: {answer}")
+
                 except Exception as e:
-                    print(f"QA model failed: {e}")
+                    print(f"❌ QA model failed: {e}")
                     continue
 
         if not qa_pairs:
+            print("⚠️ No Q&A pairs generated.")
             return "⚠️ No Q&A pairs generated."
 
+        print("✅ Final Q&A generated successfully.")
         return "\n\n".join(qa_pairs)
 
     except Exception as e:
+        print(f"🔥 Exception in generate_qa(): {e}")
         return f"❌ Error: {str(e)}"
 
 
-
 # ✅ Ask question using token (semantic similarity)
 def ask_question(token, question):
     try: